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      "text": "Human oversight shall aim at preventing or minimizing the risks to health, safety or fundamental rights that may emerge when a high-risk AI system is used. EU's proposed AI law",
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      "text": "The risk management system shall consist of a continuous iterative process run throughout the entire life cycle of a high-risk AI system, requiring regular systematic updating. EU's proposed AI law",
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      "text": "The risk management system shall consist of a continuous iterative process run throughout the entire life cycle of a high-risk AI system, requiring regular systematic updating.",
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      "text": "Like the proposed EU legislation, China also requires ongoing monitoring. China's interim measure states, \"Before using generative AI products to provide services to the public, a security assessment must be submitted to the state cyberspace and information department [i.e., the Cyberspace Administration of China].\" Then organizations must register the algorithm on the official government website. The emerging practice of an algorithmic impact assessment (AIA) can document decision making, demonstrate due diligence, and reduce present and future regulatory risk and other liability. Creating an AIA must be a cross-functional endeavor. Besides legal, GC should involve information security, data management, data science, privacy, compliance and the relevant business units to get a fuller picture of risk. Since legal leaders typically don't own the business process they recommend controls for, consulting the relevant business units is vital. The White House blueprint calls for organizations to make such assessments \"public whenever possible.\" Canada's existing Directive on Automated Decision Making, which requires Canadian government organizations to conduct AIAs, includes a tool that guides organizations through the process — starting with an assessment of risk areas such as the reasons for automation as well as the source and type of data used.",
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      "text": "Keep humans in the loop of AI development; regulatory measures call for it. That means establishing controls for humans to view, explore and calibrate AI system behavior. Where possible, these systems should be able to spell out why a particular result was achieved — sometimes called explainable AI — so users understand AI decisions. Legal leaders should mandate that third-party solution procurement and internal AI initiative development include the use of human-in-the-loop tactics to provide explainability and decrease risk. AI-mature organizations are much more likely to involve legal teams in the AI development process, specifically in coming up with ideas for AI use cases. The GC could also establish a digital ethics advisory board of legal, operations, IT, marketing and outside experts to help project teams manage ethical issues. The White House blueprint notes that independent ethics committees can both review initiatives in advance and monitor them to check whether \"any use of sensitive data\" infringes on consumer rights.",
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